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Jeff Campbell - Volunteer with the Chesapeake Bay NERR, Maryland
Name: Jeff Campbell
Briefly describe the types of volunteer activities you participate in for the NERRS. If you have a favorite volunteer topic or activity, please describe.
Primarily, I have been involved with research studies including stream macro invertebrates, fish surveys, vernal pool census and a controlled experiment measuring wild rice productivity under different conditions. I have developed a data warehouse including almost a million records of weather, tide and other data relevant to many research projects. Analysis of these factors can now easily be included with project specific data. I have also been merging larger scale geographic information systems (GIS) data with local data for analysis. I am member of the Jug Bay Wetlands Sanctuary Scientific Advisory Committee.
What life experiences led you to volunteer with the NERRS?
A long history of volunteer work with various organizations combined with curiosity about the Chesapeake Bay ecosystems led me to volunteer for a spring marsh clean up project in 2005. I discovered that volunteers here could play an important role in long term monitoring research. As a result, I have spent hundreds of hours volunteering at Jug Bay since then.
What is the most unusual or most unexpected thing that has happened to you while volunteering for the NERRS?
The most unexpected thing that has happened is a change in career direction. I have an undergraduate science degree that I had never used professionally in my information technology career. My volunteer work, particularly with the database and data mining, revealed opportunities integrating improved computer systems with ecological research. I am now a research scientist in an academic environmental research center.
What is your proudest achievement as a volunteer?
The data warehouse integrates data from a half dozen diverse sources. It provides the opportunity to use sophisticated analytical techniques commonly referred to as “data mining” to investigate ecological phenomena. For example, the impact of weather and related factors on salamander migration or the rate of turtle movement can now be easily explored. Since most data mining has used business data, I plan to develop new data mining techniques that are particularly appropriate for ecological data. |
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Last Updated on: 01-23-2009
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